Energy Conversion and Management, Vol.182, 178-190, 2019
Integrated sizing of hybrid PV-wind-battery system for remote island considering the saturation of each renewable energy resource
The proliferation of renewable energy particularly the combination of solar-wind power and storage bank, is likely to be occupied throughout the world, to mitigate the local energy concerns, improve the energy supply opportunities for off-grid communities and vitiate environmental pollution concerns as well as ease the intensity of energy consumption. To mitigate the disharmony between renewable energy (RE) generation and supply, a cost-optimal autonomous hybrid renewable energy system is developed and comparatively analyzed, considering the saturation level of each involved RE source based on various technical and economic key indicators. This study proposes a mathematical model to comprehensively analyze the effect of varying saturation, i.e. increasing the saturation of one resource meanwhile decreasing the ratio of other resource, on battery bank size, state of charge (SOC), loss of power supply, excess energy, net present cost, levelized cost of energy (COE) and payback time. A saturation factor is introduced, from 0 to 1 value with step size 0.02, where zero represents the wind-only system and one represents the solar-only system. Three different systems are considered, with different wind turbine sizes (total 150 configurations), to comparatively analyze the different energy systems and the result reveals that smaller wind turbine size (2 kW) with 90% saturation of wind energy is the most cost-effective system for the proposed remote island. In addition, the solar-alone and wind-alone systems are compared, showing that the wind-only system can provide good performance as compare to solar-only. Furthermore, the effects of the saturation factor on COE, battery bank size, SOC, excess energy, system reliability and different load demands are analyzed. Energy balance analysis of whole year and simulation performance of the system is accomplished to verify the system reliability. Sensitivity analysis reveals that wind energy, battery cost and load has a significant impact on COE than other factors.